On the Electrophysiology and Mapping of Intramural Arrhythmic Focus
Bibliographic record
Abstract
BACKGROUND: Conventional mapping of focal ventricular arrhythmias relies on unipolar electrogram characteristics and early local activation times. Deep intramural foci are common and associated with high recurrence rates following catheter-based radiofrequency ablation. We assessed the accuracy of unipolar morphological patterns and mapping surface indices to predict the site and depth of ventricular arrhythmogenic focal sources. METHODS: An experimental beating-heart model used Langendorff-perfused, healthy swine hearts. A custom 56-pole electrode array catheter was positioned on the left ventricle. A plunge needle was placed perpendicular in the center of the grid to simulate arrhythmic foci at variable depths. Unipolar electrograms and local activation times were generated. Simulation models from 2 human hearts were also included with grids positioned simultaneously on the endocardium-epicardium from multiple left ventricular, septal, and outflow tract sites. RESULTS: A unipolar Q or QS complex lacks specificity for superficial arrhythmic foci, as this morphology pattern occupies a large surface area and is the predominant pattern as intramural depth increases without developing a R component. There is progressive displacement from the arrhythmic focus to the surface exit as intramural focus depth increases. A shorter total activation time over the overlying electrode array, larger surface area within initial 20 ms activation, and a dual surface breakout pattern all indicate a deep focus. CONCLUSIONS: Displacement from the focal intramural origin to the exit site on the mapping surface could lead to erroneous lesion delivery strategies. Traditional unipolar electrogram features lack specificity to predict the intramural arrhythmic source; however, novel endocardial-epicardial mapping surface indices can be used to determine the depth of arrhythmic foci.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".